





"""simple docstring"""





import numpy as np
import torch
from torch.utils.data import Dataset

from utils import logger






class    _lowerCAmelCase  (	a			):
       """simple docstring"""




       def __init__(       self       ,					__UpperCAmelCase       ,					__UpperCAmelCase ):



         '''simple docstring'''

         lowerCAmelCase__     :Tuple											=				params

         lowerCAmelCase__     :str											=				np.array(__UpperCAmelCase )
         lowerCAmelCase__     :Tuple											=				np.array([len(__UpperCAmelCase ) for t in data] )

         self.check()
         self.remove_long_sequences()
         self.remove_empty_sequences()
         self.remove_unknown_sequences()
         self.check()
         self.print_statistics()






       def __getitem__(       self       ,					__UpperCAmelCase ):



         '''simple docstring'''

         return (self.token_ids[index], self.lengths[index])






       def __len__(       self ):



         '''simple docstring'''

         return len(self.lengths )






       def 	snake_case		(       self ):



         '''simple docstring'''

         assert len(self.token_ids ) == len(self.lengths )
         assert all(self.lengths[i] == len(self.token_ids[i] ) for i in range(len(self.lengths ) ) )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Any											=				self.params.max_model_input_size
         lowerCAmelCase__     :Tuple											=				self.lengths > max_len
         logger.info(F"Splitting {sum(__UpperCAmelCase )} too long sequences." )

         def divide_chunks(__UpperCAmelCase       ,					__UpperCAmelCase ):
           return [l[i : i + n] for i in range(0       ,					len(__UpperCAmelCase )       ,					__UpperCAmelCase )]

         lowerCAmelCase__     :str											=				[]
         lowerCAmelCase__     :Union[str, Any]											=				[]
         if self.params.mlm:
           lowerCAmelCase__				,							lowerCAmelCase__     :Tuple											=				self.params.special_tok_ids['cls_token'], self.params.special_tok_ids['sep_token']
         else:
           lowerCAmelCase__				,							lowerCAmelCase__     :Dict											=				self.params.special_tok_ids['bos_token'], self.params.special_tok_ids['eos_token']

         for seq_, len_ in zip(self.token_ids       ,					self.lengths ):
           assert (seq_[0] == cls_id) and (seq_[-1] == sep_id), seq_
           if len_ <= max_len:
             new_tok_ids.append(seq_ )
             new_lengths.append(len_ )
           else:
             lowerCAmelCase__     :Optional[int]											=				[]
             for sub_s in divide_chunks(seq_       ,					max_len - 2 ):
               if sub_s[0] != cls_id:
                 lowerCAmelCase__     :Optional[int]											=				np.insert(__UpperCAmelCase       ,					0       ,					__UpperCAmelCase )
               if sub_s[-1] != sep_id:
                 lowerCAmelCase__     :Optional[int]											=				np.insert(__UpperCAmelCase       ,					len(__UpperCAmelCase )       ,					__UpperCAmelCase )
               assert len(__UpperCAmelCase ) <= max_len
               assert (sub_s[0] == cls_id) and (sub_s[-1] == sep_id), sub_s
               sub_seqs.append(__UpperCAmelCase )

             new_tok_ids.extend(__UpperCAmelCase )
             new_lengths.extend([len(__UpperCAmelCase ) for l in sub_seqs] )

         lowerCAmelCase__     :Union[str, Any]											=				np.array(__UpperCAmelCase )
         lowerCAmelCase__     :Optional[Any]											=				np.array(__UpperCAmelCase )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Tuple											=				len(self )
         lowerCAmelCase__     :List[Any]											=				self.lengths > 1_1
         lowerCAmelCase__     :str											=				self.token_ids[indices]
         lowerCAmelCase__     :List[str]											=				self.lengths[indices]
         lowerCAmelCase__     :int											=				len(self )
         logger.info(F"Remove {init_size - new_size} too short (<=11 tokens) sequences." )






       def 	snake_case		(       self ):



         '''simple docstring'''

         if "unk_token" not in self.params.special_tok_ids:
           return
         else:
           lowerCAmelCase__     :Optional[int]											=				self.params.special_tok_ids['unk_token']
         lowerCAmelCase__     :Optional[Any]											=				len(self )
         lowerCAmelCase__     :Optional[Any]											=				np.array([np.count_nonzero(a == unk_token_id ) for a in self.token_ids] )
         lowerCAmelCase__     :List[Any]											=				(unk_occs / self.lengths) < 0.5
         lowerCAmelCase__     :Union[str, Any]											=				self.token_ids[indices]
         lowerCAmelCase__     :str											=				self.lengths[indices]
         lowerCAmelCase__     :Union[str, Any]											=				len(self )
         logger.info(F"Remove {init_size - new_size} sequences with a high level of unknown tokens (50%)." )






       def 	snake_case		(       self ):



         '''simple docstring'''

         if not self.params.is_master:
           return
         logger.info(F"{len(self )} sequences" )
         # data_len = sum(self.lengths)
         # nb_unique_tokens = len(Counter(list(chain(*self.token_ids))))
         # logger.info(f'{data_len} tokens ({nb_unique_tokens} unique)')

         # unk_idx = self.params.special_tok_ids['unk_token']
         # nb_unknown = sum([(t==unk_idx).sum() for t in self.token_ids])
         # logger.info(f'{nb_unknown} unknown tokens (covering {100*nb_unknown/data_len:.2f}% of the data)')






       def 	snake_case		(       self       ,					__UpperCAmelCase ):



         '''simple docstring'''

         lowerCAmelCase__     :Any											=				[t[0] for t in batch]
         lowerCAmelCase__     :Optional[Any]											=				[t[1] for t in batch]
         assert len(__UpperCAmelCase ) == len(__UpperCAmelCase )

         # Max for paddings
         lowerCAmelCase__     :str											=				max(__UpperCAmelCase )

         # Pad token ids
         if self.params.mlm:
           lowerCAmelCase__     :Tuple											=				self.params.special_tok_ids['pad_token']
         else:
           lowerCAmelCase__     :str											=				self.params.special_tok_ids['unk_token']
         lowerCAmelCase__     :Optional[int]											=				[list(t.astype(__UpperCAmelCase ) ) + [pad_idx] * (max_seq_len_ - len(__UpperCAmelCase )) for t in token_ids]
         assert len(tk_ ) == len(__UpperCAmelCase )
         assert all(len(__UpperCAmelCase ) == max_seq_len_ for t in tk_ )

         lowerCAmelCase__     :List[Any]											=				torch.tensor(tk_ )  # (bs, max_seq_len_)
         lowerCAmelCase__     :List[str]											=				torch.tensor(__UpperCAmelCase )  # (bs)
         return tk_t, lg_t






'''simple docstring'''







import socket







def 						_A      ( ):






   '''simple docstring'''







   A__       =     socket.socket(socket.AF_INET      ,socket.SOCK_STREAM						)
   A__       =     socket.gethostname()
   A__       =     12312

   sock.connect((host, port)						)
   sock.send(B'Hello server!'						)

   with open('Received_file'      ,'wb'						) as out_file:
      print('File opened'						)
      print('Receiving data...'						)
      while True:
         A__       =     sock.recv(1024						)
         if not data:
            break
         out_file.write(UpperCAmelCase						)

   print('Successfully received the file'						)
   sock.close()
   print('Connection closed'						)


if __name__ == "__main__":
    main()


